Use Of Surface Features Research Articles

Use of Surface Features with Controlled Kinetics to Verify Fits of Scanning Electrochemical Microscopy Images

Scanning Electrochemical Microscopy (SECM) is a promising technique for measuring kinetics of redox reactions at surfaces. The conversion of the current map - produced by rastering an electrode over the surface - to a maps of the rate constant of reactions at the surface requires computer modelling and statistical techniques. Experimentally obtained SECM images are necessary to validate computer models that will be used to test these fitting procedures.The largest challenge was finding or creating samples that have reactive sites of known kinetics that were sufficiently slow to be activation-limited. This was achieved by producing small precious metal electrodes embedded in an insulating surface. The exchange currents of these electrodes were characterized using cyclic voltammetry at high scan rates[1,2] so that the rate constant of the electrodes could be effectively controlled by the potential at which they were poised. SECM images of these electrodes can compared to computer simulations to verify that they produced correct results. [1] Nicholson, R.S. Theory and Application of Cyclic Voltammetry for Measurement of Electrode Reaction Kinetics. Anal. Chem. 1965, 37, 11, 1351–1355[2] Mirkin, M.V.; Bard, A.J. Simple Analysis of Quasi-Reversible Steady-State Voltammograms. Anal. Chem. 1992, 64, 19, 2293–2302

Surface Defect Detection Methods for Industrial Products: A Review

The comprehensive intelligent development of the manufacturing industry puts forward new requirements for the quality inspection of industrial products. This paper summarizes the current research status of machine learning methods in surface defect detection, a key part in the quality inspection of industrial products. First, according to the use of surface features, the application of traditional machine vision surface defect detection methods in industrial product surface defect detection is summarized from three aspects: texture features, color features, and shape features. Secondly, the research status of industrial product surface defect detection based on deep learning technology in recent years is discussed from three aspects: supervised method, unsupervised method, and weak supervised method. Then, the common key problems and their solutions in industrial surface defect detection are systematically summarized; the key problems include real-time problem, small sample problem, small target problem, unbalanced sample problem. Lastly, the commonly used datasets of industrial surface defects in recent years are more comprehensively summarized, and the latest research methods on the MVTec AD dataset are compared, so as to provide some reference for the further research and development of industrial surface defect detection technology.

Engaging students in analyzing and interpreting data to construct mathematical models: an analysis of students’ reasoning in a method of initial rates task

Models related to the topic of chemical kinetics are critical for predicting and explaining chemical reactivity. Here we present a qualitative study of 15 general chemistry students’ reasoning about a method of initial rates task. We asked students to discuss their understanding of the terms rate law and initial rate, and then analyze rate and concentration data in order to construct a rate law. We also asked participants to critique rate laws constructed by hypothetical students. We discuss five patterns in the students’ approach to the method of initial rates task, ranging from the use of surface-features, such as stoichiometric coefficients in the construction of a rate law, to more sophisticated interpretations and mathematization of the trends in the data. Findings highlight specific difficulties with inter-related competences required to engage in the task, such as interpreting data and reasoning mathematically, and provide insight into assessment strategies for similar tasks.